Design of intelligent travel route selection system based on multi-objective genetic algorithm

Abstract

In recent years, with the continuous improvement of people's living standards and the widespread popularity of private cars, the demand for urban residents to choose to drive to the suburbs in their spare time is growing. Visitors can choose their own tourist destinations according to their individual needs, and they can also flexibly choose the traffic routes and tourist order of scenic spots according to the road traffic status and tourist flow information of scenic spots. How to dynamically select the optimal tourist route by using the real-time information of roads and scenic spots to avoid travel congestion and queue of scenic spots has become the primary problem of suburban tourism. At present, the ways to solve road traffic problems are mainly divided into two categories: strengthening road construction, increasing road capacity, developing intelligent transportation system and improving road operation efficiency. However, under the condition of limited urban land resources, it is undoubtedly the most effective way to optimize road traffic organization and management through intelligent transportation system. In this paper, the multi-objective genetic algorithm is applied to the tourism route planning in scenic spots, and a multi-objective route planning model of scenic spots is designed. According to the different travel time periods, different methods are used, that is, the multi-objective route planning model of scenic spots is used in the peak season of tourism, and the multi-objective genetic algorithm is used to plan the route in the off season of tourism. Multi-objective genetic algorithm is the most suitable algorithm to solve tourism problems. Once again, the mathematical modeling method is used to describe it in mathematical language. According to the mathematical model, a multi-objective algorithm is designed to solve the shortest path problem. By analyzing and comparing with the previous experience of parameter selection, appropriate parameter values are selected for the multi-objective algorithm to solve the problem, and the optimal solution is obtained. The results show that the optimized route solved in this paper obviously shortens the total distance of tourists' tour routes, improves the efficiency of tourism, and at the same time reduces the consumption of the whole tour process.